We compare the proposed enhancement method with the baseline RGB images, and popular state-of-the-art enhancement approaches: (1) guided filtering (GF) [1]}, (2) bilateral filtering (BF) [2]}, [3]}, (3) image sharpening filter (IMSHARP), (4) WLS [4]}, (5) fused BF and WLS filter (BFWLS_AVG) [5]}. In BFWLS_AVG, Sharma et al. [5]} apply BF and WLS filters on the NIR channel, and retain an average of two for each pixel, similar to [5]}, instead we employ their technique in the RGB image. For a fair comparison, we compare all the methods under the same evaluation protocol discussed above. For the evaluation, we use the same parameters for feature extraction and classifier training for all methods. We did not optimize the parameters for the BF, GF, WLS, IMSHARP, and BFWLS_AVG and used the default parameters for each method. The source code for fast BF http://people.csail.mit.edu/sparis/bf/, WLS http://www.cs.huji.ac.il/\(\sim \) danix/epd/ and BFWLS_AVG https://vivoutlaw.github.io/CIC_RGB_NIR_Codes.zip are publicly available, and others are available in the Matlab framework. For comprehensive discussion of different methods, we refer the reader to [3]}, [4]}, [1]}, [5]}.
